Download Genetics of Complex Disease - Association for Molecular Pathology

Genetics of Complex
Disease
Bert Gold, Ph.D., F.A.C.M.G
Complex versus Mendelian
Trait
• Complex trait suggests the involvement of:
– Multiple loci and/or
– Environmental effects
Characteristics of complex
traits
• May be difficult to determine
– May require measurements
– Instruments
– Phenotype details may be expensive to
collect
– Affected may be well defined, the
unaffected may not
Mendelian trait suggests
• Single locus
– May have some genetic heterogeneity
– Or reduced penetrance but,
– Strong genotype-phenotype correlation
Complex traits are common
• They may cluster in families, but not
demonstrate an obvious Mendelian pattern
• Phenotypes may derive from multiple genes
and environment acting in concert
• e.g. depression, schizophrenia,
cardiovascular disease, dyslexia.
• Complex traits have substantial impact on
public health.
• Mendelian traits are rare.
How do you know a complex
phenotype is genetic?
• Mendelian disorders
– Recognizable inheritance patterns
– Phenotypic expression is highly correlated with
genotype at the disease locus
• Complex disorders
– Qualitative or Quantitative Traits
– Qualitative
• Presence or Absence
– Breast Cancer
– Bipolar Disease
How do you know a complex
phenotype is genetic?
• In complex traits, absence  unaffected
• Phenotypes are defined as above a
threshold value
• Obesity => BMI 27 kg/m
• Diabetes=> Fasting plasma glucose >
126 mg
• Threshold for affection status may be
somewhat arbitrary.
Quantitative Traits
• Measurements
– Height, Weight, BMI
– Fasting plasma glucose
– Blood pressure
• Scales
–
–
–
–
Mini-mental status examination (MMSE)
Autism Diagnostic Interview – Revised (ADI-R)
Risk Scores
Evidence for a genetic component?
More about Complex Traits
• Usually have no distinct inheritance pattern
• High frequency in the general population
complicates determining who carries the
genetic liability within a family
• Phenotypic expression modified by the
genotype of several loci and environmental
factors.
Genetic Dissection of a
complex disease
• Requires
– Clinical definitions
– Study design perspectives
– Statistical approaches
– Molecular approaches
– Social, legal, and ethical issues
discussions and clearances
The Literature Review
• How was the disease defined/diagnosed in
previous studies?
• How does this compare with your clinical
methods?
• Were individuals of all ages studied or only
one age group?
• What races were studied?
• What environmental factors were
considered?
• Significant deviations from your own definition
of phenotype and study may necessitate you
repeat these analyses.
Approaches to Determining the
Genetic Component of a
Disease
• First, establish evidence of a familial
component
• Second, determine the cause of familial
aggregation
• Third, identify the specific genetic
factors involved
Methodology for Establishing
the Genetic Component
• Segregation analysis
– Computer/labor intensive statistical tool
(SAGE, PAP) used to examine inheritance
patterns for a disease.
– By comparing different models, you can
determine which inheritance model
provides the “best fit” to your data
Segregation Model
• Advantages:
– When successful, it provides a genetic
model for linkage analysis.
– Confirms that major gene is present before
investing in expensive genomic screening.
• Simple example assuming autosomal dominant
inheritance
Segregation Model
• Disadvantages:
– Modeling is usually limited to 1-2 loci
– Sensitive to ascertainment bias
• Examples of sensitivity to ascertainment bias
– Sampling may include lost of “sporadic” families,
not appropriate for linkage analysis
– What do “negative” results imply?
– Confounders can include heterogeneity, multilocus
models
Familial clustering/recurrence
risk to relatives
• Familial aggregation is the clustering of
affected individuals within families.
• Methods for determining familial aggregation
include:
• Family history approach (Khoury et al., 1993)
Family History Approach
Specifically
Ascertain the presence or absence of a family history of
the disease in the study participants.
Three variations depending on the level of detail of
information obtained on the relatives:
Abbreviated family history
Detailed family history
Family Study
Family History Approach 2x2
If you are performing a case-control
study, you can treat family history as a
“risk-factor” and use a standard 2x2 table
to assess the significance
Family History
+
If table is
Disease in
study participant
Odds ratio= (a*d)/(b*c)
-
+
a
b
-
c
d
Correlation coefficients
• Quantitative traits can be plotted using a
trait value in one relative versus
another.
• The slope of the line is the square of the
correlation coefficient.
• If no correlation, then environmental
factors predominate.
R2 example
• Specifically,
• e.g.
80
70
60
Mean
Offspring 50
40
height 30
height
20
If you have a quantitative
trait, you can polot the trait
value in one relative versus
the other
10
0
40
45
50
55
60
65
70
Mean Parental Height
The slope of the line is the
square of the correlation coefficient.
This graph suggests that mean offspring
height is primarily a consequence of
hereditary factors.
Recurrence Risk to relatives
• A measure of how “genetic” a trait or disease
is. What is the rate of affection for relative of
proband with the disease versus the
frequency of the disease in the in the general
population? (Risch, N. Am. J. Hum. Genet.
(1990): 46: 222-253.
R 
recurrence rate in relative of proband
rate in general population
where ' R' indicates the degree of relationsh ip
• Sibling Recurrence Risk: S
Interpretation of S
• Values > 1.0 are generally taken to indicate
evidence in favor of a genetic component. In
general, the higher the value, the stronger the
genetic component.
• Values can be used to estimate the number
of genes under different genetic models.
• Note that the magnitude of the estimate is
very dependent on the frequency in the
population. For example, a common disorder
may have frequency estimates of 3-6%
depending on how a given study was
performed but this results in small lambda.
Twin and adoption studies
• Twins are special cases of siblings
– MZ twins share 100% of their genetic
material
– DZ twins share 50% of their genetic
material (same as other sibs).
Twin Studies Continued
• Comparisons of Disease concordance
rates between MZ and DZ twins provide
information regarding the involvement of
genetics
– Concordance rates with MZ>DZ are
consistent with the involvement of genetics
First Twin Study Example
Examples: One twin is affected, how often is
the other affected?
MZ
DZ
90%
90%
100%
25%
Type of
Disease
Probably
environment
al
Mendelian
recessive
deviation from the expected frequencies may
be due to incomplete penetrance
Second Twin Example
MZ
DZ
Type of
Disease
80%
16%
??
72%
35%
??
7%
7%
*
*Especially may be the same as the population frequency;
Therefore this may not be a good model for hereditary disease.
Twin Studies
• Twin studies are believed to control for
many confounding environmental
effects:
– Age
– Common familial environment
• Objection: Applicable for childhood, but not
necessarily prenatal and rarely true for adult
exposures
Cautions on Twin Studies
• Misclassification of zygosity
Placenta Chorion
Amnion
DZ(%)
MZ(%)
2
2
2
50
15
1
2
2
50
15
1
1
2
-
70
1
1
1
-
rare
• Control for sex
• Diseases with variable age of onset
Adoption Studies
• Like twin studies, adoption studies can be
used to test for evidence of genetic versus
common familial environmental factors in the
etiology of a disease.
• Cases are ascertained and the frequency of
the disease in the biological parents of the
case is compared with than in the adoptive
parents.
• Difficulties include:
– Achieving the necessary sample size
– Similarity of adoptive and biological parental
environments
Adoptive Twin Approach
Variation on Twin Studies, ‘Twins Reared Apart’. Should be very
sensitive at teasing out environmental vs. hereditary causes of
disease.
Frequency of
Frequency of
disease in biological disease in adoptive
parents
parents
Possible Etiology
85%
4%
Implies genetic
etiology, frequency
in adoptive parents
may reflect general
population risk
85%
Implies common
environment is the
primary risk factor
4%
Heritability
• A statistical measure of the degree to which a
trait is genetically determined
• Conceptual defininition: the ratio of genetic
variance to total variance
• Rigorous definition: The proportion of the total
phenotypic variance (V) of a trait that is due to
genetic variance (G). This is heritability in the
“broad sense”. It is a form of Principal
Components Analysis.
Heritability
• Approach: Compare variation among different
classes of relatives to that predicted by
simple genetic factors
• Variance can also be broken down into
additive, dominant, and epistatic variance.
• Correlation coefficient revisited: heritability=
fraction of genes shared via identity by
descent times the r squared. This represents
heritability in the narrow sense (additive
variance).
• Heritability can be more rigorously defined in
twin studies:
• h2=2(rMZ2-rDZ2)
Co-occurrence with other
genetic conditions
• This occasionally occurs in a subset of
patients and can provide very useful clues to
the location of disease genes.
– Examples:
– Association between Trisomy 21 and Alzheimers
disease led to the isolation of the APP gene.
– Association between chromosome 15q11-q13
duplications and inversions with autistic disorder
provides one of the most promising candidate
regions for an autistic disorder locus.
Experimental systems
• Animal Models
– The occurrence of a human disease trait in
a model system can provide support for the
genetic basis of human disease, and a
method for investigating the genetic
mechanisms.
• Example:
– Over 40 mouse gene have been implicated in NTD
(Harris and Juriloff, Teratology 56:177-187 (1997)).
Inheritance mode
consideration (with statistical
implications)
• Mendelian subsets?
– Early onset?
– More severe?
– Clear-cut transmission allows parametric
transmission analysis?
Consider Study Design
• Affected sibling pair
– Easy to collect?
• Affected relative pair/extended pedigree
– Better for fine mapping?
– Allows consideration of different genetic
models?
Family triads
• TDT or some variant?
• Assist with fine mapping?
• Include families not necessarily multiplex?
• Increase generality of results?
Case-control
• Easy to collect?
• Problems with establishing good
control group?
The TDT
• As a test for linkage, can use singleton
families, affected sib families, and
extended families
• Looks only for informative familial
relationships
• Has greater sensitivity than linkage
analysis or affected sib pairs
A TDT example
•79 parents heterozygous for Class I allele at insulin gene polymorphism
•(other alleles = X)
•Triad results: 24 transmitted class I, 10 transmitted X
•Affected Sib Pair Families:
•15 transmitted class I to both children
•24 transmitted class I to one child and X to the other
•6 transmitted X to both children
nontransmitting
1
trans
mittin 1
g
x
x
78
46
(78  46) 2
TDT 
78  46
 8.26
p  value  0.004
Evidence of linkage with the TDT
Allele-sharing test is not significant
For linkage (p-value=0.20)
Special populations
• Homogeneity?
• Generality?
Advantages and
Disadvantages of the TDT
• Advantages
– Can use singleton data
– Can be more powerful than ASP tests
(even when the same data are used)
• Disadvantage
– Has little power to detect linkage unless
there is also allelic association
Subject Recruitment
– Researchers responsibility to subjects
• Maintaining IRB protocols ensuring adequate
review and oversight of project
• Sharing results with subjects?
• Maintaining contact through
– Newsletters?
– Web site?
– Phone access?
Sample Collection
• Blood for DNA
• Cell Lines
• Other tissue to allow extraction of tissue
specific RNA
– e.g., muscle biopsy for muscular dystrophy
or tumor tissue for cancer research, FMRP
through scalp hairlet bulbs.
Molecular Design
• Genomic Screen
• Candidate gene analysis
– Candidate-by-function?
– Candidate-by-location?
– SSCP to screen or sequencing for more
accurate gene assessment?
• Expression studies
Translation to Clinical Care
• DNA for presymptomatic and/or
diagnostic testing?
• Develop prevention/treatment/cure?
• Phamacogenetics initiatives?